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Circumvent deep copy of context in PredictModelPlugin #334

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Merged
charlesbluca merged 2 commits into from
Nov 30, 2021
+7 −5
Merged

Circumvent deep copy of context in PredictModelPlugin #334

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f774264
Circumvent deep copy of context in PredictModelPlugin
charlesbluca Nov 29, 2021
25c121d
Check that context is not altered by predict temporary table
charlesbluca Nov 29, 2021
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9 changes: 4 additions & 5 deletions dask_sql/physical/rel/custom/predict.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,3 @@
import copy
import logging
import uuid
from typing import TYPE_CHECKING
Expand Down Expand Up @@ -88,8 +87,7 @@ def convert(
else: # pragma: no cover
continue

tmp_context = copy.deepcopy(context)
tmp_context.create_table(temporary_table, predicted_df)
context.create_table(temporary_table, predicted_df)

sql_ns = org.apache.calcite.sql
pos = sql.getParserPosition()
Expand All @@ -112,8 +110,9 @@ def convert(
None, # hints
)

sql_outer_query = tmp_context._to_sql_string(outer_select)
df = tmp_context.sql(sql_outer_query)
Comment on lines -115 to -116
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@VibhuJawa VibhuJawa Nov 29, 2021

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Seems reasonable to me but can we should a test to ensure we have not broken anything. Like are we sure that sql_outer_query does not add anything .

Maybe we add a test to verify that the registered tables still line up and nothing temporary is left around.

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@charlesbluca charlesbluca Nov 29, 2021

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Good idea, I will add that in now

sql_outer_query = context._to_sql_string(outer_select)
df = context.sql(sql_outer_query)
context.drop_table(temporary_table)

cc = ColumnContainer(df.columns)
dc = DataContainer(df, cc)
Expand Down
3 changes: 3 additions & 0 deletions tests/integration/test_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,8 +26,11 @@ def check_trained_model(c, model_name=None):
)
"""

tables_before = c.schema["root"].tables.keys()
result_df = c.sql(sql).compute()

# assert that there are no additional tables in context from prediction
assert tables_before == c.schema["root"].tables.keys()
assert "target" in result_df.columns
assert len(result_df["target"]) > 0

Expand Down